The skyline of counterfactual explanations for machine learning decision models

• Main Authors: Wang, Yongjie, Ding, Qinxu, Wang, Ke, Liu, Yue, Wu, Xingyu, Wang, Jinglong, Liu, Yong, Miao, Chunyan
• Other Authors: School of Computer Science and Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2022
• Subjects: Engineering::Computer science and engineering; Counterfactual Explanations; Multi-Objective Optimization
• Online Access: https://hdl.handle.net/10356/156946
• Institution: Nanyang Technological University

Counterfactual explanations are minimum changes of a given input to alter the original prediction by a machine learning model, usually from an undesirable prediction to a desirable one. Previous works frame this problem as a constrained cost minimization, where the cost is defined as L1/L2 distance...